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A Predictive Model of Digital Information Engagement: Forecasting User Engagement With English Words by Incorporating Cognitive Biases, Computational Linguistics and Natural Language Processing
This study introduces and empirically tests a novel predictive model for digital information engagement (IE) - the READ model, an acronym for the four pivotal attributes of engaging information: Representativeness, Ease-of-use, Affect, and Distribution.
Words That Stick: Predicting Decision Making and Synonym Engagement Using Cognitive Biases and Computational Linguistics
This research draws upon cognitive psychology and information systems studies to anticipate user engagement and decision-making on digital platforms.
The Ways of Words: The Impact of Word Choice on Information Engagement and Decision Making
The framework was empirically validated in a large-scale user study measuring how word choice impacts the dimensions of IE.
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